We have been investigating a number of biophysical processes associated with nerve excitation and their relationship to the MR signal. Uri Nevo, a former STBB post-doctoral fellow, and now an Assistant Professor at Tel Aviv University, successfully constructed and tested an experimental system in our lab to interrogate organotypic cultured brain slices using diffusion MRI. This work showed promising results relating changes in the measured apparent diffusion coefficient (ADC) map to changes in environmental conditions to which cultured tissues were subjected. One hypothesis that emerged from these studies is that active processes occurring at many different length scales (cell streaming, water flow across membranes, etc.) are responsible for some signal loss in the diffusion weighted MRI signal. This insight prompted the development of a theory to explain how microscopic fluid flows affect the measured diffusion weighted MRI signal and the ADC measured in tissues (i.e., pseudo-diffusion) and an experimental model system, the Rheo-NMR, in which well-characterized flow fields can be produced, which create known amounts of pseudo-diffusion. The importance of these combined studies is that if such microscopic motions, like streaming, water flow across membranes, etc., manifest themselves as an additional signal loss in diffusion weighted MRI experiments, then we can use this information to infer different aspects of cell function and vitality, including excitability. We are now continuing these studies with a recently hired graduate student from the University of Maryland, Ruiliang Bai. We have also been collaborating with Bradley Roth to try to examine different physical mechanisms that could be exploited or used to detect neural currents directly using MRI. One approach we examined previously was whether small displacements caused by Lorentz forces produced in strong magnetic fields (like those within a large clinical MRI scanner) could be employed to measure neural currents in vivo using MRI. Our calculations showed that the induced displacements of nerves caused by Lorentz forces in tissues would be too small to be detectable by MRI using existing technology. In the area of Transcranial Magnetic Stimulation (TMS), Pedro Miranda and his group in Lisbon, in association with STBB, has performed detailed calculations using the finite element method (FEM), to predict the electric field and current density distributions induced in the brain during TMS. Previously, we found that both tissue heterogeneity and anisotropy of the electrical conductivity (i.e., the conductivity tensor field) contribute significantly to distort these induced fields, and even to create excitatory or inhibitory "hot spots" in some regions that were previously not predicted. More recently, we have been developing more realistic FEM models of cortical folds, containing gyri and sulci. We showed that this more complicated cortical anatomy also significantly affects the distribution of induced electric fields within the tissue, and the location and types of nerve cells that could be excited or depressed by such stimuli. These phenomena could have significant clinical consequences both in interpreting or inferring the region or locus of excitation and in determining the source of nerve excitation. We are beginning to marry our macroscopic models of TMS with microscopic models of nerve excitability in the CNS in order to predict the locus of excitation in TMS and even the populations of neurons that are excited or depressed. Recently, we have also been applying these advance FEM models to explain the physical basis for Direct Current Excitation (DCE).